Multiplex communications – Communication over free space – Combining or distributing information via code word channels...
Reexamination Certificate
1998-12-03
2001-08-14
Nguyen, Chau (Department: 2663)
Multiplex communications
Communication over free space
Combining or distributing information via code word channels...
C375S349000
Reexamination Certificate
active
06275485
ABSTRACT:
BACKGROUND OF THE INVENTION
I. Field of the Invention
The invention relates generally to wireless communications. More particularly, the invention relates to signal characterization in a wireless communication system.
II. Description of the Related Art
In a typical wireless communication system, a plurality of remote units communicate through a common base station.
FIG. 1
is a block diagram showing a typical modern wireless communication system
10
. The system is comprised of a series of base stations
14
. A set of remote units
12
communicate with the base stations
14
. The remote units
12
communicate with the base stations
14
over a forward link channel
18
and a reverse link channel
20
. For example,
FIG. 1
shows a hand-held portable telephone, a vehicle mounted mobile telephone and a fixed location wireless local loop telephone. Such systems offer voice and data services. Other modern communication systems operate over wireless satellite links rather than through terrestrial base stations.
In order for multiple remote units to communicate over a common channel, a means of multiplexing the signal onto the forward link and reverse link channels must be used. One commonly used method is code division multiple access (CDMA). Additional information concerning CDMA is set forth in the TIA/EIA Interim Standard entitled “Mobile Station—Base Station Compatibility Standard for Dual-Mode Wideband Spread Spectrum Cellular System,” TIL/EIA/IS-95-A, and its progeny, the contents of which are incorporated herein by reference. In a CDMA system, the forward and reverse link signals are modulated with a spreading code which spreads the signal energy over a band of frequencies. By correlating the incoming signal with the spreading sequences used in the transmitting units, the signals which are transmitted in the same frequency band at the same time can be distinguished from one another at the receiving unit.
In general, CDMA systems operate most efficiently when each remote unit receives the forward link signal at the minimum signal quality which is necessary in order to accurately decode the incoming signal. If the forward link signal arrives at the remote unit at a level that is too low, the signal level may not be sufficient to support reliable communications. If the forward link signal arrives at the remote unit at a level that is too high, the signal acts as unnecessary interference to other remote units. Therefore, the remote unit monitors the signal quality at which the signal is received and requests an increase in the power level at which the base station transmits the forward link signal if the signal quality is too low and requests a decrease in the power level at which the base station transmits the forward link signal if the signal quality is above the threshold.
In order to implement such a system, in one embodiment, the remote unit estimates the forward link signal quality by determining the signal-to-noise ratio at which it receives the forward link signal. The signal-to-noise ratio can be determined by finding the ratio of the energy per bit to the non-orthogonal noise power density E
b
/N
t
). The energy per bit is a measure of the energy associated with a single information bit. Typically, signal-to-noise ratios are determined over a series of bits so that an average energy per bit is determined and used as the numerator of the signal-to-noise ratio.
FIG. 2
is a block diagram of a receiver which determines an average energy per bit. A decoder
30
receives a signal vector {right arrow over (r)} corresponding to a series of N symbols which make up a frame such that {right arrow over (r)}=(r
1
, r
2
, . . . , r
N
). Each symbol, r
n
, is comprised of a signal portion and a noise portion as shown in Equation 1 below.
r
n
=s
n
+w
n
(Eq. 1)
wherein:
r
n
is a voltage value of the n
th
symbol;
s
n
is the signal portion of the n
th
symbol in volts; and
w
n
, is the noise portion of the n
th
symbol in volts. The signal component of each bit sample can be expressed in terms of a voltage level and a polarity as shown in Equation 2.
r
n
=A
n
d
n
+w
n
(Eq. 2)
wherein:
A
n
is the absolute value of the voltage level of the n
th
symbol; and
d
n
represents the polarity (i.e., digital value) of the n
th
symbol (i.e., +/−1). In a digital representation, the voltage level A
n
is transmitted into a numerical value represented by digital bits.
Referring again to
FIG. 2
, the decoder
30
receives the symbols corresponding to a frame represented by the vector {right arrow over (r)} and converts them to a series of bits. In one embodiment, the decoder
30
is a Viterbi decoder. Typically, the bits output by the decoder
30
are passed to subsequent processing stages (not shown) in order to recreate a transmitted signal. In order to determine the energy associated with the signal energy in the frame, the bits output by the decoder are re-encoded by a re-encoder
32
which operates in a complimentary manner with the decoder
30
such that the output of the re-encoder
32
is the vector {right arrow over (d)}=(d
1
, d
2
, . . . d
N
) where d
n
represents the polarity of the n
th
symbol as defined above.
The vector {right arrow over (r)} and the vector {right arrow over (d)} are input into a dot product block
34
. The dot product block
34
takes the dot product of the two inputs as shown in Equation 3 below.
1
N
(
r
→
·
d
→
)
=
1
N
(
r
1
*
d
1
+
r
2
*
d
2
+
…
+
r
N
*
d
N
)
(Eq. 3)
The output of the square of the dot product block
34
is coupled to a squaring block
36
yielding the result given in Equation 4.
1
N
(
r
→
·
d
→
)
2
=
1
N
[
(
A
1
d
1
+
w
1
)
*
d
1
+
(
A
2
d
2
+
w
2
)
+
d
2
+
…
(
A
N
d
N
+
w
N
)
*
d
N
]
2
(Eq. 4)
Note that d
n
2
=1 for all n. We can also assume that the noise component of the vector {right arrow over (r)} is a series of independent and identically distributed random variables with zero mean, possibly Gaussian distribution, and, thus, according to well-known principles of stochastic processes, randomly multiplying the individual components by +/−1 does not change the characteristics or average value of the noise. In this way, Equation 4 reduces to Equation 5A as shown below.
1
N
(
r
→
·
d
→
)
2
=
(
1
N
∑
n
=
1
N
A
n
+
1
N
∑
n
=
1
N
w
n
)
2
=
(
1
N
∑
n
=
1
N
A
n
+
ϵ
)
2
(Eq. 5A)
The second term of Equation 5A is, by definition, the mean noise component of the vector {right arrow over (r)} and is equal to zero such that Equation 5A reduces to Equation 5B as shown below.
1
N
(
r
→
·
d
→
)
2
=
1
N
∑
n
=
1
N
A
n
2
(Eq. 5b)
Thus, the output of the square of the dot product block
34
shows the sum of the energy of the symbols in the frame which is directly related to the energy in each bit of the frame as shown in Equation 6 below.
E
b
=({right arrow over (r)}·{right arrow over (d)})
2
/B (Eq. 6)
wherein: B is the number of bits in a frame.
In order to determine the signal-to-noise ratio, an estimate of the noise component of the signal must also be determined. In general, we are only interested in the non-orthogonal portion of the noise, N
t
, because any orthogonal portion of the noise can be removed by signal processing. Non-orthogonal noise sources include thermal noise, forward link transmissions from neighboring base stations and multipath propagations from the servicing base station. Estimation of the non-orthogonal component of the noise is more difficult than the estimation of the bit energy in general. Although several techniques have been discussed, they tend to be inaccurate or require an excessive amount of processing resources. For example, one means of determining the non-orthogonal noise energy is disclosed in U.S. Pat. No.
Beladi S. Hossain
English Sean
Nguyen Chau
Nguyen Phuongchau Ba
Qualcomm Inc.
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